IMPLICATION OF HUMAN ACTIVITIES ON LAND USE LAND
IMPLICATION OF HUMAN ACTIVITIES ON LAND USE LAND COVER DYNAMICS INKAGERA CATCHMENT, EAST AFRICAByRobel Ogbaghebriel BerakhiB.S., University of Asmara, 2004A ThesisSubmitted in Partial Fulfillment of the Requirements for theMaster of Science DegreeDepartment of Geography and Environmental Resourcesin the Graduate SchoolSouthern Illinois University CarbondaleDecember 2013
THESIS APPROVALIMPLICATION OF HUMAN ACTIVITIES ON LAND USE LAND COVER DYNAMICS INKAGERA CATCHMENT, EAST AFRICAByRobel Ogbaghebriel BerakhiA Thesis Submitted in PartialFulfillment of the Requirementsfor the Degree ofMaster of Sciencein the field of Geography & Environmental ResourcesApproved by:Dr. Tonny Oyana, ChairDr. Samuel Adu-PrahDr. Guangxing WangGraduate SchoolSouthern Illinois University CarbondaleOctober 14, 2013
AN ABSTRACT OF THE THESIS OFRobel Ogbaghebriel Berakhi, for the Masters of Science degree in GEOGRAPHY &ENVIRONMENTAL RESOURCES, presented on October 14, 2013, at Southern IllinoisUniversity Carbondale.TITLE: IMPLICATION OF HUMAN ACTIVITIES ON LAND USE LAND COVERDYNAMICS IN KAGERA CATCHMENT, EAST AFRICAMAJOR PROFESSOR: Dr. Tonny J. OyanaThe Kagera basin in East Africa has experienced major land surface loss in tropicalforests, woodlands, and savannas due to the conversion of land for agricultural purposes. Thishas resulted in soil degradation, siltation, eutrophication, desertification, biodiversity loss, andclimate change. Damages in the Kagera have also led to pollution and sedimentation in VictoriaLake which receives water from the basin. These environmental changes have an effect onpeople in this region who largely depend on the natural resources. It has been indicated that theseproblems are mainly due to population growth as this region has the highest population growthand density when compared to sub-Saharan countries. However, previous studies conducted inthis region have not investigated the spatial relationship between population growth and LULCchanges. The aim of this study was to quantify LULC changes that occurred from 1984 to 2011,and predict future scenarios. Another goal of this study was to investigate the spatial relationshipbetween population growth/density and LULC changes, and its socioeconomic influences. Apost classification change detection method and Markov chain model of LULC change wereused to analyze the past and future LULC dynamics. Administrative level census data of Kagerai
was used to calculate population growth and density, and these were overlaid to LULC change.The assessment of change for the period of 1984-2011 overall showed a major expansion ofagriculture at the expense of woodland savanna. This was mainly attributed to demographic andsocioeconomic/political changes prior to and during the study period. Population growth anddensity were linked to transitions to agriculture, and agriculture dominance during the studyperiod. In addition, the oil price shocks of the 1970's that led to the adoption of StructuralAdjustment Program were implicated as the major global macroeconomic influence in the use ofresources, mainly in the agriculture sector. Internal policies such as Tanzania’s “Ujama”villagization of production, and biophysical factors such as precipitation and proximity to waterbodies were also implicated to the LULC changes. The findings in this study imply thatunderstanding inter-relationship of factors is critically important, and the issue of LULC changemust be approached in a holistic manner.ii
ACKNOWLEDGEMENTSForemost, I would like to express my sincere gratitude to my advisor Dr. Tonny Oyanafor his continuous support of my MS study and research, for his patience, motivation,enthusiasm, and immense knowledge. He guided me in all facets of my research and gave me anopportunity to grow in this department.I would also like to thank the rest of my thesis committee: Dr. Guangxing Wang and Dr.Samuel Adu-Prah for their time and willingness to be on my committee and answer anyquestions I had during my research. I want to further thank Dr. Samuel Adu-Prah as I had thepleasure and experience of being his teaching assistant during my study in this department.I also want to thank Mr. Grimay Misgna for letting me use the resources in the geologylaboratory.Last but not least I am deeply indebted to my family for their enduring love and sacrificethey made throughout my life.iii
TABLE OF CONTENTSCHAPTERPAGEABSTRACT . iACKNOWLEDGEMENTS . iiiLIST OF TABLES . viiiLIST OF FIGURES . xCHAPTER 1 – INTRODUCTION . 11.1.Rationale and problem statement . 21.2.Aim of the study . 41.3.Research questions . 5CHAPTER 2 – LITERATURE REVIEW . 62.1 Human-environment Interaction . 62.2. Land use and Land cover . 102.2.1. Causes of land use land cover change . 102.2.2. Land use and land cover detection .152.2.2.1. Image classification .152.2.2.2. Change detection .192.2.3. Land cover changes in Kagera. 21CHAPTER 3 – DATA AND METHODOLOGY . 22iv
3.1. Study area . 223.2. Data description and collection . 263.2.1. Image acquisition and preparation . 263.2.2. Population data . 283.2.3. Ancillary data . 293.3.3. Flow Chart of the methodology 303.3. Image preprocessing 313.4. Land use and Land cover classification and accuracy assessment . 333.4.1. Image classification . 333.4.2. Accuracy assessment . 363.5. Post-classification analysis . 373.5.1. Past land cover change analysis. 373.5.2. Major land cover transition .373.5.3. Land use and cover change prediction . 383.5.4. Land cover-population relationship analysis .38CHAPTER 4 – RESULTS . 394.1. Image classification and accuracy assessment . 39v
4.1.1. Land use and land cover .394.1.2. Accuracy Assessment .424.2. Land use and land cover changes in Kagera basin . 494.2.1. Past land use and land cover changes .494.2.2. Land use and cover change prediction .544.3. Population growth 594.4. Population change and Land use patterns 644.5. Land cover transitions and Hydro-geographical zones . 68CHAPTER 5 – DISSCUSION AND CONCLUSION . 705.1. Image Classification and analysis . 705.2. Implications of human activities on land use and land cover changes in Kagera . 735.2.1. Demographic factor . 745.2.2. Global macro-economic influences/implications . 775.2.3. Bio-physical factors . 825.3. Limitations . 845.4. Further studies. 845.4. Conclusion . 85REFERENCES . 87vi
APPENDIX A . 94APPENDIX B 97VITA 107vii
LIST OF TABLESTable 2.1 DPSIR frame work elements .8Table 2.2 Factors that influence land management decision of land use and land cover change . 11Table 3.1 A predominantly cloud free Landsat scene chosen for the land cover classification 27Table 3.2 Land use and land cover classes . 34Table 4.1 The areas and proportions of each land use and land cover category of the Kagerabasin for each study year 40Table 4.2 Error matrix of 1984 classified image .42Table 4.3 Accuracy totals and Kappa Statistics result for 1984 classified image . 43Table 4.4 Error matrix of 1994 classified image .44Table 4.5 Accuracy totals and Kappa Statistics result for 1994 classified image .45Table 4.6 Error matrix of 2011 classified image . 46Table 4.7 Accuracy totals and Kappa Statistics result for 2011 classified image .47Table 4.8 Cross tabulation for the period between 1984 and 1994 showing gain and losses . 53Table 4.9 Cross tabulation for the period between 1994 and 2011 showing gain and losses . 53Table 4.10 Cross tabulation for the period between 1984 and 2011 showing gain and losses . 54viii
Table 4.11 The probability of change in 2011 based on the land transition between 1984 and1994 .55Table 4.12 The amount expected to transition in 2011 based on the land transition between 1984and 1994 56Table 4.13 The amount expected to transition in 2020 based on the land transition between 1994and 2011 . 57Table 4.14 The probability of change in 2020 based on the land transition between 1994 and2011. . 57Table 4.15 The amount expected to transition in 2020 based on the land transition between 1984and 2011 . 58Table 4.16 The probability of change in 2020 based on the land transition between 1984 and2011. .59ix
LIST OF FIGURESFigure 2.1 DPSIR Framework . 7Figure 2.2 Indicators and their relationship . 9Figure 3.1a Map of Kagera basin showing neighboring countries: Uganda, Tanzania, DemocraticRepublic of Congo, and Burundi . 22Figure 3.1b Hydro geographical zones of Kagera .25Figure 3.2 Flow chart of a methodology .30Figure 3.3 Mosaicked Landsat images after radiometric correction and haze reduction .32Figure 4.1 The land use and land cover classification of Kagera basin for the years 1984, 1994and 2011 .41Figure 4.2 Gain and losses, net changes and contributors of each class for three periods .52Figure 4.3 Total population of Kagera basin for the period between 1984 and 2011 .60Figure 4.4 The population in each country in the basin . .60Figure 4.5 Actual and predicted population for the year 2002 for Rwanda .61Figure 4.6 Actual and predicted for the year 2012 for Rwanda .62Figure 4.7 Population densities of the districts within the Kagera basin .63Figure 4.8. High and low population density districts, and the Land use and cover transitions.66x
Figure 4.9 Land cover transitions for the three periods and districts with high and low populationchange . .67Figure 4.10 Hydro geographical zones of Kagera in relation to the land cover transition .69Figure 5.1 The major socioeconomic events .80xi
CHAPTER 1INTRODUCTIONLand use and land cover (LULC) describes the economic use of land and surfacefeatures, respectively (Campbell, 2007). Humans play a major role as forces of change in theenvironment, inflicting environmental change at all levels ranging from the local to the globalscale (Gamble et al., 2003). The various uses of land for economic purposes have greatlytransformed land cover at a global scale (Turner et al., 1994). Over the last 10,000 years, almosthalf of the ice-free earth surface has changed and most of the result was due to the use of land byhumans (Lambin et al., 2003; Turner et al., 2007). The production of agricultural and forestgoods specifically have caused agriculture and forestry to become the most transformative eventsglobally; with agricultural land rivaling forest cover and occupying 35% of the ice free landsurface in 2000 (Foley et al., 2007). In using land to yield goods and services, humans alterecosystems and their interactions with the atmosphere, aquatic systems, and surrounding land(Vitousek et al, 1997).LULC is one of the environmental issues mostly tightly linked to climate change in acomplex manner, and changes in both can have profound effect on an ecosystem’s ability toprovide goods and services to society (Loveland et al., 2003). Land use and cover plays a keyrole in climate changes through the exchange of greenhouse gases, sensible heat, and localevapotranspiration (Vitousek et al., 1997; Foley et al., 2005; Loveland et al., 2007).Approximately 35% of the CO2 emissions to the atmosphere were from land use (Foley et al.,2005). In addition to climate change, growth of human population and land cover changes have1
an effect on the biogeochemical cycles, habitat availability, biodiversity, soil erosion, waterquality, water flow, and sediment flows (Vitousek et al., 1997; Dale 1997; Turner et al., 1994).Africa occupies one-fifth of the global land area and many of the continent’s resourcessuch as forests, water, biodiversity, marine eco-systems have experienced changes due to bothhuman and climate change drivers (Mosha, 2011). The deforestation of tropical rain forests ofcentral Africa in general was higher in the 1980’s than in the 1990’s, and cropland expansion bysmall holders is a more prevalent form of land cover conversion in Africa (Lambin et al., 2003;Justices et al., 2001; Brink and Eva., 2009).The Kagera basin in east Africa has been one of the major locations around the worldexperiencing change in tropical forests, woodlands and savannas due to agricultural land use.Some of the consequences of these changes include soil degradation, siltation, eutrophication,desertification, biodiversity loss, and climate change. These changes have likewise beenimplicated with population growth, economic, and policy changes arising from the borderingcountries of Burundi, Uganda, Tanzania, and Rwanda (Wasige et al., 2013). The population isprojected to increase rapidly and the consequences of LULC changes remain a threat (NBI,2008).1.1. Rationale and problem statementIn Kagera, the resources and ecosystems are under pressure due to fast population growth,agricultural expansion and intensification (progressive reduction of farm sizes), andunsustainable use of land (FAO, 2013). This has caused persistence in land degradationaccompanied by a serious loss of biodiversity. The impacts on the agro-ecosystems are also2
affecting the livelihoods of the local populous since they largely depend upon natural resourcesfor their living (FAO, 2013). Moreover, degradation in water quality, the loss of wetlands,sedimentation of aquatic systems, and reduced ground and surface water supply are beingobserved. Off site, the Kagera basin is also a major contributor of inflow to Victoria Lake (thesecond largest fresh water lake in the world). The changes in the Kagera basin have contributedto the pollution and sedimentation of Victoria Lake (Tamatamah, 2004).The above mentioned problems have been related to population growth, as well as economicand policy changes arising from the bordering countries of Burundi, Uganda, Tanzania andRwanda (Wasige et al., 2013; Tolo et al., 2012). Kagera is a heavily populated basin in the eastAfrican Rift Valley Lakes sub-region (NBI, 2008). The total population is around 15 millionwhich accounts for 40% of the total Lake Victoria basin population (NBI, 2008). The populationdensity of Kagera basin is 248, more than 8 times the average of sub-Saharan Africa (NBI,2008). The future population is projected to increase at rates of 3.4% (Rwanda), 2.3%(Tanzania) and 3.2% (Uganda), which are relatively higher compared to the average rate of othersub-Saharan countries (2.5%) (NBI, 2008).For these reasons, the Kagera basin was selected for a visual study of the physical LULCchanges at a regional level. Regional studies provide adequate spatial and temporal resolutionand account for variations in cause to cover relationships that are not explained at the globallevel (Turner et al., 1994). Past studies have attributed population growth/density as a key driver,but none have tried to link them together. This study links population to land cover transitionswith an explicit spatial component. It is also clear that causes of environmental degr
Land use and land cover (LULC) describes the economic use of land and surface features, respectively (Campbell, 2
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